The SOC in cells’ living expectations of Conway’s Game of Life and its extended version

2016 ◽  
Vol 89 ◽  
pp. 348-352 ◽  
Author(s):  
Jinling Wei ◽  
Haiyan Zhou ◽  
Jun Meng ◽  
Fan Zhang ◽  
Yunmo Chen ◽  
...  
2015 ◽  
Vol 21 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Randall D. Beer

Maturana and Varela's concept of autopoiesis defines the essential organization of living systems and serves as a foundation for their biology of cognition and the enactive approach to cognitive science. As an initial step toward a more formal analysis of autopoiesis, this article investigates its application to the compact, recurrent spatiotemporal patterns that arise in Conway's Game-of-Life cellular automaton. In particular, we demonstrate how such entities can be formulated as self-constructing networks of interdependent processes that maintain their own boundaries. We then characterize the specific organizations of several such entities, suggest a way to simplify the descriptions of these organizations, and briefly consider the transformation of such organizations over time.


2020 ◽  
Vol 26 (3) ◽  
pp. 338-365
Author(s):  
Peter D. Turney

We present a computational simulation of evolving entities that includes symbiosis with shifting levels of selection. Evolution by natural selection shifts from the level of the original entities to the level of the new symbiotic entity. In the simulation, the fitness of an entity is measured by a series of one-on-one competitions in the Immigration Game, a two-player variation of Conway's Game of Life. Mutation, reproduction, and symbiosis are implemented as operations that are external to the Immigration Game. Because these operations are external to the game, we can freely manipulate the operations and observe the effects of the manipulations. The simulation is composed of four layers, each layer building on the previous layer. The first layer implements a simple form of asexual reproduction, the second layer introduces a more sophisticated form of asexual reproduction, the third layer adds sexual reproduction, and the fourth layer adds symbiosis. The experiments show that a small amount of symbiosis, added to the other layers, significantly increases the fitness of the population. We suggest that the model may provide new insights into symbiosis in biological and cultural evolution.


1976 ◽  
Vol 23 (1) ◽  
pp. 56-60
Author(s):  
Lauren L. Meneghan

John Conway's game of “life” provides a delightful and fascinating game for students of junior high school. (The introduction to Mr. Conway's game can be found in an article by Martin Gardner in the October 1970 issue of Scientific American.) Mr. Conway intended that the game be played by one person, but it can easily be adapted so that two or three students can play the game at one time.


2009 ◽  
Vol 15 (3) ◽  
pp. 351-375 ◽  
Author(s):  
Nicholas M. Gotts

Small patterns of state 1 cells on an infinite, otherwise empty array of Conway's game of Life can produce sets of growing structures resembling in significant ways a population of spatially situated individuals in a nonuniform, highly structured environment. Ramifying feedback networks and cross-scale interactions play a central role in the emergence and subsequent dynamics of the quasi population. The implications are discussed: It is proposed that analogous networks and interactions may have been precursors to natural selection in the real world.


2001 ◽  
Vol 29 (1) ◽  
pp. 63-69
Author(s):  
Solomon Marcus

Inspired by a mathematical ecology of thearre (M. Dinu) and the eco-grammar systems (E. Csuhaj-Varju et al.), this paper gives a brief analysis of simple cellular automata games in order to demonstrate their primary semiotic features. In particular, the behaviour of configurations in Conway's game of life is compared to several general features of Uexküll's concept of Umwelt. It is concluded that ecological processes have a fundamental semiotic dimension.


2019 ◽  
Vol 8 (4) ◽  
pp. 8487-8490

In order to improve the health care reach, we need efficient and fast computer aided simulation processes or algorithms. When some change is found in pathological reports and biomedical quantities, the person is susceptible to diseases. If the diseases are detected earlier then there can be increase in the rate of mortality. Tumor is one such disease which has been seen to be one of the most fatal for human beings. Detecting and removing tumor is big challenge for medical practitioners. Medical image processing can be used through cellular automata has proven to be one of the fast and reliable method for detection of tumor cells. To study the capabilities of medical science CA’s are being used extensively, as they are useful in studying the selfreproducing biological systems. Purpose: This paper presents an algorithm for segmentation of MRI image through cellular automata, using Conway’s Game of Life. A new approach is being used in this paper, first the image is converted into gray level image. Then edge detection is done for this image using Game of Life. This edge detected image is overlapped with the gray scale image to get the resulted segmented image as an output. Materials and Methods: In order to run the proposed algorithm MATLAB2019b is used and the images are obtained. Results: Algorithm was used on different MRI’s and the results were taken.


10.37236/2611 ◽  
2013 ◽  
Vol 20 (3) ◽  
Author(s):  
Christiaan Hartman ◽  
Marijn J. H. Heule ◽  
Kees Kwekkeboom ◽  
Alain Noels

Conway's Game of Life has inspired enthusiasts to search for a wide range of patterns for this classic cellular automaton. One important challenge in this context is finding the smallest Garden of Eden (GoE), a state without a predecessor. We take up this challenge by applying two techniques. First, we focus on GoEs that contain a symmetry. This significantly reduces the size of the search space for interesting sizes of the grid. Second, we implement the search using incremental satisfiability solving to check thousands of states per second. By combining these techniques, we broke several records regarding GoEs: the fewest defined cells, the smallest bounding box, and the lowest living density. Furthermore, we established a new lower bound for the smallest GoE.


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